surjection: Fix test condition failures in probabilistic tests

[mllwchrry]

Fixes two CI failures:

• In test_input_selection where test condition failed: result < n_inputs * 10 (see https://github.com/BlockstreamResearch/secp256k1-zkp/actions/runs/23255024904/job/67611676287). The test had assertions that were stricter than the actual iteration budget.
• In test_input_selection_distribution_helper where test condition failed: result > 0 (see https://github.com/mllwchrry/secp256k1-zkp/actions/runs/23445282634/job/68207165336). Maximum iterations (64) were insufficient: ~10^-8 failure rate per call * 10,000 calls = ~0.01% failure.

[real-or-random]

@apoelstra

I can't remember why we have this randomized design where proof initialization does rejection sampling and can fail. It's explained here how it works: https://github.com/BlockstreamResearch/secp256k1-zkp/blob/master/src/modules/surjection/surjection.md#initialization But I don't see the point. Can you provide an intuition for this for context?

I mean, one could simply put the input asset at a random position in the subset and then sample some other input assets to add to the subset. The probability that this looks random can be determined mathematically and doesn't need to be estimated "experimentally".

I feel like I don't understand what's going on here.

[real-or-random]

I wonder what e is.